most citedGaussian Mixture Proposals with Pull-Push Learning Scheme to Capture Diverse Events for Weakly Supervised Temporal Video Grounding

17 citations · 25 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL20247 cited

HyperCLOVA X Technical Report

Kang Min Yoo, Jaegeun Han, Sookyo In +393

We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. H…

cs.CL2024

Topic-VQ-VAE: Leveraging Latent Codebooks for Flexible Topic-Guided Document Generation

YoungJoon Yoo, Jongwon Choi

This paper introduces a novel approach for topic modeling utilizing latent codebooks from Vector-Quantized Variational Auto-Encoder~(VQ-VAE), discretely encapsulating the rich info…

cs.CV20241 cited

Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis

Jonghyun Lee, Hansam Cho, Youngjoon Yoo +2

Addressing the limitations of text as a source of accurate layout representation in text-conditional diffusion models, many works incorporate additional signals to condition certai…

cs.CV202317 cited

Gaussian Mixture Proposals with Pull-Push Learning Scheme to Capture Diverse Events for Weakly Supervised Temporal Video Grounding

Sunoh Kim, Jungchan Cho, Joonsang Yu +2

In the weakly supervised temporal video grounding study, previous methods use predetermined single Gaussian proposals which lack the ability to express diverse events described by…

cs.CV2023

GeNAS: Neural Architecture Search with Better Generalization

Joonhyun Jeong, Joonsang Yu, Geondo Park +2

Neural Architecture Search (NAS) aims to automatically excavate the optimal network architecture with superior test performance. Recent neural architecture search (NAS) approaches…